With the aim of both supporting clinical training and further technical research, which will eventually lead to automated algorithmic analysis, the International Skin Imaging Collaboration (ISIC) developed an international repository of dermoscopic images known as the ISIC Archivehttps://www.isic-archive.com. Every year the ISIC increases its archive and promote a challenge to leverage the automated skin cancer detection. For ISIC 2019, 25,331 dermoscopy images are available for training across 8 different categories. The test dataset is composed of 8,239 images and contains an additional outlier class not represented in the training data, which the new systems must be able to identify. Beside the images, the dataset also contains meta-data for most of the images. The meta-data is composed of the patient's age and sex, and the region where the individual with the skin lesion is located. All these data come from the BCN_20000 (Department of Dermatology, Hospital Clínic de Barcelona) [1]}, HAM10000 [2]} (ViDIR Group, Department of Dermatology, Medical University of Vienna), and from an Anonymous resources [3]}. In Fig. REF  is shown some samples of skin diseases from the ISIC 2019 dataset.
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